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Basic Programming in Python II

This hands-on Python programming course offers students an opportunity to obtain proficiency in the core concepts of Python as well as the programming skills for building applications using tools from various task-specific Python libraries. The course covers important topics in computer science and information systems such as data types, reading and writing to standard IO, using operators, controlling the flow of execution, using functions, reading and writing Python source code files, basic object-oriented programming concepts, and more.

You will be introduced to preliminary topics in data science and explore the process of building a web application using Python. You will complete hands-on programming tasks using your creativity and learn how to apply Python to resolve real-world problems.

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What's inside

Syllabus

Clean Code in Python I

This module focuses on the art of writing clean Python code. Throughout this module, you will explore PEP 8 conventions and standards, and engage with a variety of coding examples. This will enable you to understand the importance of coding conventions for professional programming. By the end of this module, you should be able to put your knowledge of clean code principles into practice by writing readable, efficient, and maintainable code.

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Helps learners explore core concepts of Python such as data types, using operators, controlling the flow of execution, using functions, reading and writing Python source code files, and basic object-oriented programming concepts

Provides an opportunity to build applications using tools from various task-specific Python libraries

Covers important topics in computer science and information systems

Introduces learners to preliminary topics in data science

Offers hands-on programming tasks for learners to apply their creativity and resolve real-world problems

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Reviews summary

Practical python for intermediate developers

According to students, Basic Programming in Python II is a largely positive experience for those looking to move beyond foundational concepts. Learners particularly praise its hands-on approach and the emphasis on writing clean, maintainable code, which many find invaluable for professional development. The course effectively covers core programming concepts like advanced loops and basic object-oriented programming, with instructors often lauded for making complex topics digestible. While it introduces preliminary data science and web application building, some learners note that additional resources may be needed for deeper specialization, indicating it serves as a strong stepping stone.

Introduces advanced topics but requires further study.

"Some of the preliminary data science parts felt a bit rushed, and I'll need to seek additional resources to dive deeper."

"Good foundation, but don't expect to become a data scientist or web developer just from this course."

"The data science intro was a nice touch, but it's really just an intro. For deeper data science, you'll need more courses."

Instructors excel at explaining complex programming topics.

"The instructor explained complex topics clearly."

"Fantastic course! The instructor is brilliant, making complex topics digestible."

"I appreciated the examples and how the instructor broke down more complex ideas."

Strong focus on applying concepts to real-world problems.

"This course truly delivered on its promise of practical application. The hands-on projects were excellent, especially the sections on building a basic web application."

"I appreciated the examples and how the instructor broke down more complex ideas. The real-world problems aspect was very engaging."

"The hands-on exercises were key to my learning. I enjoyed the project-based approach."

Teaches professional coding standards and practices.

"The clean code modules were a revelation for improving my coding style, making my professional work much more readable."

"I loved how this course emphasized writing efficient and maintainable code. The PEP 8 guidelines were integrated throughout, which is crucial for industry standards."

"The focus on practical applications and clean code is incredibly valuable for anyone looking to work professionally with Python."

May require more than basic Python knowledge to keep pace.

"The prerequisites weren't clear enough; I struggled with the pace, especially with OOP concepts. It feels like it assumes more prior knowledge..."

"While the idea of clean code is great, the explanation felt dry and didn't provide enough hands-on examples for me to grasp fully."

"The web application example was interesting, but the lectures could be clearer on some of the underlying concepts. I felt a little lost without prior web dev experience."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Basic Programming in Python II with these activities:

Review data science fundamentals

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Prepare for the data science component of the course by reviewing fundamental concepts such as data types, data structures, and statistical analysis.

Browse courses on Data Science

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Revisit your notes or textbooks on data science basics.
Complete practice exercises on data manipulation and analysis.

Review Python basics

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Refresh your understanding of Python basics, including variables, data types, and control flow, to prepare for this course.

Browse courses on Python Basics

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Review online tutorials or documentation on Python basics.
Complete practice exercises on basic Python concepts.

Review 'Python Crash Course, 2nd Edition' by Eric Matthes

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Supplement your course learning by reading this comprehensive guide to Python programming, covering essential concepts, libraries, and best practices.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

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Read through the book, taking notes and highlighting key concepts.
Complete the exercises and projects provided in the book.
Apply the concepts you learn in your own Python projects.

Five other activities

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Build a simple Python script

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Apply your Python skills by creating a simple script that performs a specific task, such as data processing or text analysis.

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Identify a problem or task that can be solved using Python.
Design the script's logic and structure.
Write and test the Python code.
Document the script's functionality and usage.

Join a Python study group

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Collaborate with other students by joining a Python study group to discuss concepts, work on projects, and provide support.

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Find or create a Python study group online or through your university or local community.
Participate in regular group meetings and discussions.
Work together on projects or assignments.
Provide support and encouragement to other group members.

Follow tutorials on advanced Python libraries

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Expand your knowledge of Python libraries by following tutorials on specific libraries, such as NumPy, Pandas, or Matplotlib.

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Identify a specific Python library that aligns with your interests or course topics.
Find reputable online tutorials or courses on that library.
Follow the tutorials, complete the exercises, and experiment with the library's functionality.
Apply your newly acquired skills in your Python projects or assignments.

Solve Python coding problems

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Challenge your coding abilities by solving Python coding problems on platforms like Leetcode or HackerRank.

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Choose a problem-solving platform and select appropriate problems.
Analyze the problem statement and design an algorithm.
Implement the solution in Python and test its correctness.
Review and optimize your code for efficiency and readability.

Create a Python tutorial or blog post

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Enhance your understanding by creating a tutorial or blog post on a specific Python topic, sharing your knowledge and helping others learn.

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Choose a specific topic within Python that you are proficient in.
Research and gather relevant information and examples.
Write a clear and engaging tutorial or blog post, explaining the topic in detail.
Proofread and edit your content for clarity and accuracy.
Publish your tutorial or blog post online and share it with others.

Career center

Learners who complete Basic Programming in Python II will develop knowledge and skills that may be useful to these careers:

Software Engineer

As a Software Engineer, you will be tasked with designing, developing, and maintaining software applications. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in software development. By completing this course, you will gain proficiency in core Python concepts and learn how to apply them to real-world problems.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in data analysis. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for data analysts.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their knowledge of programming, mathematics, and statistics to extract insights from data. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in data science. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for data scientists.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models to solve real-world problems. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in machine learning. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for machine learning engineers.

See salaries and explore the career path for Machine Learning Engineer

Web Developer

Web Developers design and develop websites and web applications. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in web development. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for web developers.

See salaries and explore the career path for Web Developer

Quantitative Analyst

Quantitative Analysts use their knowledge of programming, mathematics, and statistics to develop financial models. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in quantitative finance. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for quantitative analysts.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use their knowledge of business and technology to analyze and improve business processes. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in business analysis. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for business analysts.

See salaries and explore the career path for Business Analyst

Product Manager

Product Managers are responsible for managing the development and launch of new products. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in product management. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for product managers.

See salaries and explore the career path for Product Manager

Project Manager

Project Managers are responsible for planning and executing projects. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in project management. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for project managers.

See salaries and explore the career path for Project Manager

Technical Writer

Technical Writers create and maintain technical documentation. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in technical writing. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for technical writers.

See salaries and explore the career path for Technical Writer

Data Engineer

Data Engineers design and build data pipelines to move data between different systems. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in data engineering. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for data engineers.

See salaries and explore the career path for Data Engineer

DevOps Engineer

DevOps Engineers work to bridge the gap between development and operations teams. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in DevOps. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for DevOps engineers.

See salaries and explore the career path for DevOps Engineer

Cloud Architect

Cloud Architects design and build cloud computing solutions. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in cloud computing. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for cloud architects.

See salaries and explore the career path for Cloud Architect

Security Analyst

Security Analysts are responsible for protecting computer systems from unauthorized access. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in security analysis. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for security analysts.

See salaries and explore the career path for Security Analyst

Information Security Analyst

Information Security Analysts are responsible for protecting computer systems from unauthorized access. This course may be useful in helping you build a foundation in Python programming, which is a popular language used in information security. By completing this course, you will gain proficiency in data types, operators, and control flow, which are essential skills for information security analysts.

See salaries and explore the career path for Information Security Analyst

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Basic Programming in Python II.

Python Pocket Reference

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Comprehensive guide to Python. It covers all the basics of the language, as well as more advanced topics such as object-oriented programming and data science. It good choice for students who want to learn Python in depth.

Basic Programming in Python II

Here's a deal for you

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Practical python for intermediate developers

Activities

Career center

Reading list

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